Land-use intensity and landscape structure drive the acoustic composition of grasslands

Abstract

<p>Understanding drivers and monitoring changes of biodiversity forms the basis for evidence-based management and policy recommendations that aim to reduce biodiversity loss and to ensure the delivery of ecosystem services on which we rely. Ecoacoustic monitoring can be applied across large spatial and temporal scales, offering the potential for less resource-intensive ecosystem monitoring. Indices of acoustic diversity have been shown to correlate with species richness of various taxa, as well as vegetation and landscape structure. In order to apply ecoacoustic monitoring at large scales we need to improve our understanding of the effects of local and regional land-use on acoustic patterns, and assess how temporal aspects of acoustic patterns can be integrated in these analyses. We hypothesized that land-use intensity and landscape structure affect species richness and composition of birds and orthopteran, and therefore indirectly affect acoustic diversity and composition. To test this, we set up autonomous recording systems in grassland plots along land-use intensity gradients in three regions in Germany. We applied structural equation modelling to analyze the direct and indirect drivers of acoustic diversity and composition, including mowing and grazing intensities, landscape diversity, distance to the nearest road, vascular plant species richness as well as bird and orthopteran species richness and composition. Single indices of acoustic diversity did not reflect changes in bird or orthopteran species richness, making them poor predictors for local land-use related changes in species richness in grassland plots. Acoustic composition (non-metric multidimensional scaling combination of mean monthly acoustic indices at different day phases), however, did relate to differences in landscape structure, land-use intensity, vocalizing species composition and orthopteran species richness. We propose the developed acoustic composition metric as suitable proxy to detect ecosystem changes in grasslands.</p>